DocumentCode :
2705945
Title :
Three dimensional MREIT for breast cancer detection on open MRI scanners
Author :
Li, Gang ; Chen, Ruijuan ; Hao, Liling ; Lin, Ling
Author_Institution :
State Key Lab. of Precision Meas., Technol. & Instrum, Tianjin Univ., Tianjin, China
fYear :
2012
fDate :
6-8 June 2012
Firstpage :
446
Lastpage :
450
Abstract :
Magnetic resonance electrical impedance tomography (MREIT) is a novel, noninvasive functional imaging technology that is hopeful to be applied in the diagnosis of early breast cancer. Based on the Open MRI scanners with a vertical magnetic field, the sensitivity reconstruction algorithm is developed to three dimensional space for MREIT. To cut down the computing time, the sensitivity matrix equation is solved by the Generalized Minimal Residual Krylov method for breast imaging. Simulation results with a hemisphere model show the validity and precision of the reconstruction. Phantom results based on an Open 0.36T MRI scanner show a promising application prospect for breast cancer detection by Open MREIT.
Keywords :
biomedical MRI; cancer; electric impedance imaging; image reconstruction; matrix algebra; medical image processing; object detection; breast cancer detection; breast cancer diagnosis; breast imaging; generalized minimal residual Krylov method; hemisphere model; magnetic resonance electrical impedance tomography; noninvasive functional imaging technology; open MRI scanners; sensitivity matrix equation; sensitivity reconstruction algorithm; three dimensional MREIT; vertical magnetic field; Breast cancer; Conductivity; Image reconstruction; Impedance; Magnetic resonance imaging; Open MRI; breast cancer; magnetic resonance electrical impedance tomography; three dimensional imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2012 International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4673-2238-6
Electronic_ISBN :
978-1-4673-2236-2
Type :
conf
DOI :
10.1109/ICInfA.2012.6246847
Filename :
6246847
Link To Document :
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